With the explosion of the amount of documents and the pages of documents becoming increasing larger and more numerous, readers do not have enough time to navigate the full page but also do not want to lose key information that is contained in a searched document. Users of search engines (e.g., web search engines) are often forced to sift through a long ordered list of search results in the form of documents, snippets, or text fragments, a time-consuming and inconvenient prospect in order to identify relevant topics inside the results. Existing search engines such as Google™, Yahoo™, and MSN™ often return a long list of search results ranked by relevancy to the given query. Web users must then review the list and examine the titles and (short) snippets sequentially in order to identify their desired results. This is an even more time consuming task when multiple sub-topics of the given query are mixed together. For example, when a user submits a query “jaguar” into Google and wants to get search results related to “big cats”, the user may need to go to the 10th, 11th, 32nd, and/or 71st results.
A user often needs to locate information quickly but effectively. Finding information effectively may not be efficient. For example, a user may sequentially review a document, using a find command in which the document is sequentially searched with an editor for a desired term. The user may consequently review the located section of the document and proceed to locate the next occurrence of the term if the current section is not sufficient. On the other hand, accelerating the search procedure may result in reducing the efficacy of the search.
Being able to navigate documents in an effective and efficient manner is becoming more important with the increasing number of available documents on networked computer systems. Enhanced document navigation would help in facilitating information retrieval.